Salicylic Acid and Risk of Colorectal Cancer: A Two-Sample Mendelian Randomization Study

Salicylic acid (SA) has observationally been shown to decrease colorectal cancer (CRC) risk. Aspirin (acetylsalicylic acid, that rapidly deacetylates to SA) is an effective primary and secondary chemopreventive agent. Through a Mendelian randomization (MR) approach, we aimed to address whether levels of SA affected CRC risk, stratifying by aspirin use. A two-sample MR analysis was performed using GWAS summary statistics of SA (INTERVAL and EPIC-Norfolk, N = 14,149) and CRC (CCFR, CORECT, GECCO and UK Biobank, 55,168 cases and 65,160 controls). The DACHS study (4410 cases and 3441 controls) was used for replication and stratification of aspirin-use. SNPs proxying SA were selected via three methods: (1) functional SNPs that influence the activity of aspirin-metabolising enzymes; (2) pathway SNPs present in enzymes’ coding regions; and (3) genome-wide significant SNPs. We found no association between functional SNPs and SA levels. The pathway and genome-wide SNPs showed no association between SA and CRC risk (OR:1.03, 95% CI: 0.84–1.27 and OR: 1.08, 95% CI:0.86–1.34, respectively). Results remained unchanged upon aspirin use stratification. We found little evidence to suggest that an SD increase in genetically predicted SA protects against CRC risk in the general population and upon stratification by aspirin use.

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Salicylic acid and risk of colorectal cancer: a two sample Mendelian randomization study

10.1101/2021.10.13.21262206 ◽

2021 ◽

Author(s):

Aayah Nounu ◽

Rebecca C Richmond ◽

Isobel D Stewart ◽

Praveen Surendran ◽

Nicholas J. Wareham ◽

...

Keyword(s):

Colorectal Cancer ◽

Salicylic Acid ◽

Genome Wide Association Study ◽

Mendelian Randomization ◽

Significant Snps ◽

Nucleotide Polymorphisms ◽

Functional Snps ◽

Genome Wide ◽

Inverse Variance ◽

Colon Cancer Family Registry

Background Salicylic acid (SA) is a metabolite that can be obtained from the diet via fruit and vegetable ingestion, of which increased consumption has observationally been shown to decrease risk of colorectal cancer (CRC). Whilst primary prevention trials of SA and CRC risk are lacking, there is strong evidence from clinical trials and prospective cohort studies that aspirin (acetylsalicylic acid) is an effective primary and secondary chemopreventative agent. Since aspirin is rapidly deacetylated to form SA, it follows that SA may have a central role for aspirin chemoprevention. Through a Mendelian randomization (MR) approach, we aimed to address whether levels of SA affected CRC risk, and whether aspirin intake as a proxy for increased SA levels was required to identify an effect. Methods and Findings A two sample MR analysis was carried out using genome-wide association study summary statistics of SA from INTERVAL and EPIC-Norfolk (N= 14,149) and CRC from Colon Cancer Family Registry (CCFR), Colorectal Cancer Transdisciplinary Study (CORECT), Genetics and Epidemiology of Colorectal Cancer (GECCO) consortia and UK Biobank (55,168 cases and 65,160 controls). The Darmkrebs: Chancen der Verhütung durch Screening (DACHS) study (4,410 cases and 3,441 controls) was used for replication and stratification of aspirin-users and non-users. Single nucleotide polymorphisms (SNPs) for SA were selected via three methods: (1) Functional SNPs that influence aspirin and SA metabolising enzymes' activity; (2) Pathway SNPs, those that are present in the coding regions of genes involved in aspirin and SA metabolism; and (3) genome-wide significant SNPs associated with levels of circulating SA. No association was found between the functional SNPs and SA levels, therefore they were not taken forward in an MR analysis. We identified 2 pathway SNPs (explaining 0.03% of the variance in SA levels and with an F statistic of 1.74) and 1 genome-wide independent SNP (explaining 0.05% of the variance and with an F statistic of 7.44) to proxy for SA levels. Using the pathway SNPs, an inverse variance weighted approach found no association between an SD increase in SA and CRC risk (GECCO OR:1.03, 95% CI: 0.84-1.27 and DACHS OR:1.10, 95% CI:0.58-2.07) and no association was found upon stratification between aspirin users and non-users in the DACHS study (OR:0.93, 95% CI:0.23-3.73 and OR:1.24, 95% CI:0.57-2.69, respectively). Wald ratio results using the genome-wide SNP also showed no association between an SD increase in SA and CRC risk (GECCO OR: 1.08, 95% CI:0.86-1.34 and DACHS OR: 1.01, 95% CI:0.44-2.31) and no effect was observed upon stratification by aspirin use (users OR:0.66, 95% CI: 0.11-4.12 and non-users OR: 1.12, 95% CI: 0.42-2.97). Conclusions We found no evidence to suggest that an SD increase in genetically predicted SA protects against CRC risk in the general population and upon stratification by aspirin use. However, based on the calculated variance explained by the SNPs and the F statistic, we acknowledge the possibility of weak instrument bias and the need to find better instruments for SA levels.

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Causal effect of renal function on venous thromboembolism: a two-sample Mendelian randomization investigation

Journal of Thrombosis and Thrombolysis ◽

10.1007/s11239-021-02494-4 ◽

2021 ◽

Author(s):

Shuai Yuan ◽

Maria Bruzelius ◽

Susanna C. Larsson

Keyword(s):

Renal Function ◽

Venous Thromboembolism ◽

Mendelian Randomization ◽

Causal Effect ◽

Meta Analysis ◽

Genome Wide Association Studies ◽

Uk Biobank ◽

Genome Wide ◽

Increased Risk ◽

Mr Study

AbstractWhether renal function is causally associated with venous thromboembolism (VTE) is not yet fully elucidated. We conducted a two-sample Mendelian randomization (MR) study to determine the causal effect of renal function, measured as estimated glomerular filtration rate (eGFR), on VTE. Single-nucleotide polymorphisms associated with eGFR were selected as instrumental variables at the genome-wide significance level (p < 5 × 10−8) from a meta-analysis of 122 genome-wide association studies including up to 1,046,070 individuals. Summary-level data for VTE were obtained from the FinnGen consortium (6913 VTE cases and 169,986 non-cases) and UK Biobank study (4620 VTE cases and 356,574 non-cases). MR estimates were calculated using the random-effects inverse-variance weighted method and combined using fixed-effects meta-analysis. Genetically predicted decreased eGFR was significantly associated with an increased risk of VTE in both FinnGen and UK Biobank. For one-unit decrease in log-transformed eGFR, the odds ratios of VTE were 2.93 (95% confidence interval (CI) 1.25, 6.84) and 4.46 (95% CI 1.59, 12.5) when using data from FinnGen and UK Biobank, respectively. The combined odds ratio was 3.47 (95% CI 1.80, 6.68). Results were consistent in all sensitivity analyses and no horizontal pleiotropy was detected. This MR-study supported a casual role of impaired renal function in VTE.

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Associations of observational and genetically determined caffeine intake with coronary artery disease and diabetes

European Heart Journal ◽

10.1093/ehjci/ehaa946.1493 ◽

2020 ◽

Vol 41 (Supplement_2) ◽

Author(s):

A Said ◽

Y.J Van De Vegte ◽

N Verweij ◽

P Van Der Harst

Keyword(s):

Coronary Artery Disease ◽

Coronary Artery ◽

Mendelian Randomization ◽

Cox Regression ◽

Caffeine Intake ◽

Uk Biobank ◽

Genome Wide ◽

Artery Disease ◽

Genetically Determined

Abstract Background Caffeine is the most widely consumed psychostimulant and is associated with lower risk of coronary artery disease (CAD) and type 2 diabetes (T2D). However, whether these associations are causal remains unknown. Objectives This study aimed to identify genetic variants associated with caffeine intake, and to investigate possible causal links between genetically determined caffeine intake and CAD or T2D. Additionally, we aimed to replicate previous observational findings between caffeine intake and CAD or T2D. Methods Genome wide associated studies (GWAS) were performed on caffeine intake from coffee, tea or both in 407,072 UK Biobank participants. Identified variants were used in a two-sample Mendelian randomization (MR) approach to investigate evidence for causal links between caffeine intake and CAD in CARDIoGRAMplusC4D (60,801 cases; 123,504 controls) or T2D in DIAGRAM (26,676 cases; 132,532 controls). Observational associations were tested within UK Biobank using Cox regression analyses. Results Moderate observational caffeine intakes from coffee or tea were associated with lower risks of CAD or T2D compared to no or high intake, with the lowest risks at intakes of 120–180 mg/day from coffee for CAD (HR=0.77 [95% CI: 0.73–0.82; P<1e-16]), and 300–360 mg/day for T2D (HR=0.76 [95% CI: 0.67–0.86]; P=1.57e-5). GWAS identified 51 novel genetic loci associated with caffeine intake, enriched for central nervous system genes. In contrast to observational analyses, MR analyses in CARDIoGRAMplusC4D and DIAGRAM yielded no evidence for causal links between caffeine intake and the development of CAD or T2D. Conclusions MR analyses indicate caffeine intake might not protect against CAD or T2D, despite protective associations in observational analyses. Manhattan_plot_CaffeineIntake Funding Acknowledgement Type of funding source: None

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Intake of Processed Meat, but Not Sodium, Is Associated With Risk of Colorectal Cancer: Evidence From Observational Study in UK Biobank and Two-Sample Mendelian Randomization

SSRN Electronic Journal ◽

10.2139/ssrn.3768694 ◽

2021 ◽

Author(s):

Qi Feng ◽

Sunny H. Wong ◽

Jie Zheng ◽

Qian Yang ◽

Joseph JY Sung ◽

...

Keyword(s):

Colorectal Cancer ◽

Observational Study ◽

Mendelian Randomization ◽

Processed Meat ◽

Uk Biobank

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Estimating Effect Sizes and Expected Replication Probabilities from GWAS Summary Statistics

10.1101/032474 ◽

2015 ◽

Author(s):

Dominic Holland ◽

Yunpeng Wang ◽

Wesley K Thompson ◽

Andrew Schork ◽

Chi-Hua Chen ◽

...

Keyword(s):

Association Studies ◽

Significant Snps ◽

Effect Sizes ◽

Genome Wide Association Studies ◽

Summary Statistics ◽

Sample Sizes ◽

Genetic Components ◽

Complex Phenotypes ◽

Genome Wide ◽

Z Scores

Genome-wide Association Studies (GWAS) result in millions of summary statistics (``z-scores'') for single nucleotide polymorphism (SNP) associations with phenotypes. These rich datasets afford deep insights into the nature and extent of genetic contributions to complex phenotypes such as psychiatric disorders, which are understood to have substantial genetic components that arise from very large numbers of SNPs. The complexity of the datasets, however, poses a significant challenge to maximizing their utility. This is reflected in a need for better understanding the landscape of z-scores, as such knowledge would enhance causal SNP and gene discovery, help elucidate mechanistic pathways, and inform future study design. Here we present a parsimonious methodology for modeling effect sizes and replication probabilities that does not require raw genotype data, relying only on summary statistics from GWAS substudies, and a scheme allowing for direct empirical validation. We show that modeling z-scores as a mixture of Gaussians is conceptually appropriate, in particular taking into account ubiquitous non-null effects that are likely in the datasets due to weak linkage disequilibrium with causal SNPs. The four-parameter model allows for estimating the degree of polygenicity of the phenotype -- the proportion of SNPs (after uniform pruning, so that large LD blocks are not over-represented) likely to be in strong LD with causal/mechanistically associated SNPs -- and predicting the proportion of chip heritability explainable by genome wide significant SNPs in future studies with larger sample sizes. We apply the model to recent GWAS of schizophrenia (N=82,315) and additionally, for purposes of illustration, putamen volume (N=12,596), with approximately 9.3 million SNP z-scores in both cases. We show that, over a broad range of z-scores and sample sizes, the model accurately predicts expectation estimates of true effect sizes and replication probabilities in multistage GWAS designs. We estimate the degree to which effect sizes are over-estimated when based on linear regression association coefficients. We estimate the polygenicity of schizophrenia to be 0.037 and the putamen to be 0.001, while the respective sample sizes required to approach fully explaining the chip heritability are 106and 105. The model can be extended to incorporate prior knowledge such as pleiotropy and SNP annotation. The current findings suggest that the model is applicable to a broad array of complex phenotypes and will enhance understanding of their genetic architectures.

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Educational attainment impacts drinking behaviors and risk for alcohol dependence: results from a two-sample Mendelian randomization study with ~780,000 participants

Molecular Psychiatry ◽

10.1038/s41380-019-0535-9 ◽

2019 ◽

Cited By ~ 4

Author(s):

Daniel B. Rosoff ◽

Toni-Kim Clarke ◽

Mark J. Adams ◽

Andrew M. McIntosh ◽

George Davey Smith ◽

...

Keyword(s):

Alcohol Use ◽

Educational Attainment ◽

Alcohol Dependence ◽

Mendelian Randomization ◽

Association Studies ◽

Significant Snps ◽

Genome Wide Association Studies ◽

Reverse Causality ◽

Genome Wide ◽

Genetic Instruments

Abstract Observational studies suggest that lower educational attainment (EA) may be associated with risky alcohol use behaviors; however, these findings may be biased by confounding and reverse causality. We performed two-sample Mendelian randomization (MR) using summary statistics from recent genome-wide association studies (GWAS) with >780,000 participants to assess the causal effects of EA on alcohol use behaviors and alcohol dependence (AD). Fifty-three independent genome-wide significant SNPs previously associated with EA were tested for association with alcohol use behaviors. We show that while genetic instruments associated with increased EA are not associated with total amount of weekly drinks, they are associated with reduced frequency of binge drinking ≥6 drinks (ßIVW = −0.198, 95% CI, −0.297 to –0.099, PIVW = 9.14 × 10−5), reduced total drinks consumed per drinking day (ßIVW = −0.207, 95% CI, −0.293 to –0.120, PIVW = 2.87 × 10−6), as well as lower weekly distilled spirits intake (ßIVW = −0.148, 95% CI, −0.188 to –0.107, PIVW = 6.24 × 10−13). Conversely, genetic instruments for increased EA were associated with increased alcohol intake frequency (ßIVW = 0.331, 95% CI, 0.267–0.396, PIVW = 4.62 × 10−24), and increased weekly white wine (ßIVW = 0.199, 95% CI, 0.159–0.238, PIVW = 7.96 × 10−23) and red wine intake (ßIVW = 0.204, 95% CI, 0.161–0.248, PIVW = 6.67 × 10−20). Genetic instruments associated with increased EA reduced AD risk: an additional 3.61 years schooling reduced the risk by ~50% (ORIVW = 0.508, 95% CI, 0.315–0.819, PIVW = 5.52 × 10−3). Consistency of results across complementary MR methods accommodating different assumptions about genetic pleiotropy strengthened causal inference. Our findings suggest EA may have important effects on alcohol consumption patterns and may provide potential mechanisms explaining reported associations between EA and adverse health outcomes.

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Gene-based association analysis identified 190 genes with polymorphisms affecting neuroticism

10.1101/2020.08.06.240721 ◽

2020 ◽

Author(s):

Nadezhda M. Belonogova ◽

Irina V. Zorkoltseva ◽

Yakov A. Tsepilov ◽

Tatiana I. Axenovich

Keyword(s):

Gene Expression ◽

Detailed Analysis ◽

Association Analysis ◽

Genetic Variants ◽

Bioinformatics Analysis ◽

Summary Statistics ◽

Uk Biobank ◽

Protein Coding ◽

Pathogenic Variants ◽

Genome Wide

AbstractRecent genome-wide studies have reported about 600 genes potentially influencing neuroticism. Little is known about the mechanisms of their action. Here, we aimed to conduct a more detailed analysis of genes whose polymorphisms can regulate the level of neuroticism. Using UK Biobank-based GWAS summary statistics, we performed a gene-based association analysis using four sets of genetic variants within a gene differing in their protein coding properties. To guard against the influence of strong GWAS signals outside the gene, we used the specially designed procedure. As a result, we identified 190 genes associated with neuroticism due to their polymorphisms. Thirty eight of these genes were novel. Within all genes identified, we distinguished two slightly overlapping groups comprising genes that demonstrated association when using protein-coding and non-coding SNPs. Many genes from the first group included potentially pathogenic variants. For some genes from the second group, we found evidence of pleiotropy with gene expression. We demonstrated that the association of almost two hundred known genes could be inflated by the GWAS signals outside the gene. Using bioinformatics analysis, we prioritized the neuroticism genes and showed that the genes influencing the trait by their polymorphisms are the most appropriate candidate genes.

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Cancer PRSweb – an Online Repository with Polygenic Risk Scores (PRS) for Major Cancer Traits and Their Phenome-wide Exploration in Two Independent Biobanks

10.1101/2020.01.22.915751 ◽

2020 ◽

Cited By ~ 1

Author(s):

Lars G. Fritsche ◽

Snehal Patil ◽

Lauren J. Beesley ◽

Peter VandeHaar ◽

Maxwell Salvatore ◽

...

Keyword(s):

Association Studies ◽

Predictive Performance ◽

Risk Scores ◽

P Value ◽

Genome Wide Association Studies ◽

Summary Statistics ◽

Uk Biobank ◽

Polygenic Risk ◽

Genome Wide ◽

Study Results

AbstractTo facilitate scientific collaboration on polygenic risk scores (PRS) research, we created an extensive PRS online repository for 49 common cancer traits integrating freely available genome-wide association studies (GWAS) summary statistics from three sources: published GWAS, the NHGRI-EBI GWAS Catalog, and UK Biobank-based GWAS. Our framework condenses these summary statistics into PRS using various approaches such as linkage disequilibrium pruning / p-value thresholding (fixed or data-adaptively optimized thresholds) and penalized, genome-wide effect size weighting. We evaluated the PRS in two biobanks: the Michigan Genomics Initiative (MGI), a longitudinal biorepository effort at Michigan Medicine, and the population-based UK Biobank (UKB). For each PRS construct, we provide measures on predictive performance, calibration, and discrimination. Besides PRS evaluation, the Cancer-PRSweb platform features construct downloads and phenome-wide PRS association study results (PRS-PheWAS) for predictive PRS. We expect this integrated platform to accelerate PRS-related cancer research.

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HOPS: a quantitative score reveals pervasive horizontal pleiotropy in human genetic variation is driven by extreme polygenicity of human traits and diseases

Genome Biology ◽

10.1186/s13059-019-1844-7 ◽

2019 ◽

Vol 20 (1) ◽

Cited By ~ 9

Author(s):

Daniel M. Jordan ◽

Marie Verbanck ◽

Ron Do

Keyword(s):

Genetic Variation ◽

Genetic Architecture ◽

Genome Wide Association ◽

Summary Statistics ◽

Human Genetic Variation ◽

Uk Biobank ◽

Multiple Traits ◽

Genome Wide ◽

Quantitative Score ◽

Independent Effects

Abstract Horizontal pleiotropy, where one variant has independent effects on multiple traits, is important for our understanding of the genetic architecture of human phenotypes. We develop a method to quantify horizontal pleiotropy using genome-wide association summary statistics and apply it to 372 heritable phenotypes measured in 361,194 UK Biobank individuals. Horizontal pleiotropy is pervasive throughout the human genome, prominent among highly polygenic phenotypes, and enriched in active regulatory regions. Our results highlight the central role horizontal pleiotropy plays in the genetic architecture of human phenotypes. The HOrizontal Pleiotropy Score (HOPS) method is available on Github at https://github.com/rondolab/HOPS.

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